Modelling Long term Goals Debjanee Barua*, Judy Kay*, Bob Kummerfeld*, and Cecile Paris** * School of IT, University of Sydney, Australia, 2006 ** CSIRO Computa1onal Informa1cs, chai:: Computer human adapted interac1on research group Goals and user modelling •  User modelling and personalisa1on research frequently states that it aims to model people’s goals, along with other such core aspects as knowledge, interests, traits and context •  But we could not find a paper describing a user model representa-on for long term goals eg I want to: –  be a competent C programmer •  I want to be able to write C linked lists –  to learn sta1s1cs •  know how to do a t-­‐test –  become physically fiUer •  achieve the recommended levels of physical ac1vity •  and avoid unhealthy levels of inac1vity chai:: Computer human adapted interac1on research group Many tools for ‘Goal seWng’ chai:: 3 Computer human adapted interac1on research group With no rigorously designed representa-on of user models for long term goals …. •  We studied theories of goal seWng •  We used these to inform the design of a generic user model –  and iden1fied addi1onal goal-­‐specific aspects •  We concluded that it essen1al to involve the user in many aspects of defining their long term goals –  So we designed an interface to enable users to manage their goal user model chai:: Computer human adapted interac1on research group Key contribu1ons •  Representa1on for –  a theore1cally grounded generic model for user’s goals –  Iden1fica1on of those aspects that should be augmented with domain specific elements –  Defining those elements that user needs to specify •  Design of User Interface needed for these aspects •  Inves1gated the Usability of the interface and Usefulness of the Goal Model –  In-­‐lab Think Aloud (16 par1cipants) –  In-­‐the-­‐wild 4 week field study (14 par1cipants) chai:: 5 Computer human adapted interac1on research group Representa1on of Goal Model •  Draw upon psychological theories –  SMART goals –  Social Cogni1ve Model –  Metacogni1on –  Self determina1on Theory E. A. Locke and G. P. Latham. Building a prac1cally useful theory of goal seWng and task mo1va1on: A 35-­‐year odyssey. American Psych., 57(9):705-­‐-­‐717, 2002. A. Bandura. Social cogni1ve theory of self-­‐regula1on. Organiza1onal behavior and human decision processes, 50(2):248-­‐-­‐287, 1991. Edward L. Deci and Richard M. Ryan. Self-­‐Determina1on. John Wiley & Sons, Inc., 2010. chai:: Computer human adapted interac1on research group Goal model components -­‐ SMART •  Target value –  e.g. do 150 minutes moderate ac1vity every week •  Dura,on –  e.g. start from today, for 4 weeks (though 4 weeks is good default for many long term goals) •  Measuring tools –  e.g. Fitbit, Smart cushion, desktop sensor, phone app •  Data/evidence –  e.g. ac1vity level each minute; 1mes user is inac1ve •  Subgoals –  e.g increasing moderate ac1vity and avoiding inac1vity are relevant subgoals for achieving healthy levels of physical ac1vity Bold indicates the user needs to provide the value Italics means that domain-­‐specific informa1on, for this class of goal, to guide the user Blue is generic for all models chai:: Computer human adapted interac1on research group Goal model components -­‐ extrinsic •  Reminder –  e.g. email/tweet/SMS, every day at noon, triggered alerts •  Rewards or Punishment –  e.g. scores, badges, messages •  Social involvement –  compe--ve, coopera-ve –  people involved –  what to share with each –  data from them for comparison Bold indicates the user needs to provide the value Italics means that domain-­‐specific informa1on, for this class of goal, to guide the user Blue is generic for all models chai:: Computer human adapted interac1on research group Goal model components -­‐ intrinsic • 
• 
• 
• 
• 
Importance Difficulty Commitment Self efficacy Self sa-sfac-on The same scale, Likert 1 ..7 is reasonable for all cases (even though Bandura used a different scale) Bold indicates the user needs to provide the value Italics means that domain-­‐specific informa1on, for this class of goal, to guide the user Blue is generic for all models chai:: Computer human adapted interac1on research group Addi1onal notes •  Anything the user wants to log at any -me –  e.g., “I was sick today” – as the user wants to note that in rela1on to the goal Bold indicates the user needs to provide the value Italics means that domain-­‐specific informa1on, for this class of goal, to guide the user Blue is generic for all models chai:: 10 Computer human adapted interac1on research group Architecture – place of goals in our implemented system for goals associated with healthy levels of physical ac-vity chai:: Computer human adapted interac1on research group Walk through the interface we created For the case of a set of goals around ac1vity and inac1vity, Using sensors: FitBit, smart cushion, desktop sensor chai:: Computer human adapted interac1on research group chai:: 13 Computer human adapted interac1on research group chai:: 14 Computer human adapted interac1on research group User studies to evaluate goal seWng interface chai:: Computer human adapted interac1on research group Performance hypotheses –  H1: Users can set SMART goal elements with our Goal Interface –  H2: Users can set extrinsic and intrinsic elements with our Goal Interface Affec1ve hypotheses –  H3: Users consider the Goal Interface easy to use to set goals –  H4: Users consider the Goal Interface helps them think about their wellness goals. chai:: Computer human adapted interac1on research group Study Design Study Preliminary Lab Think Aloud -­‐-­‐ Associated ques1onnaire Start of the field trial -­‐-­‐ Associated ques1onnaire Week 4 Field Goal Review Week 8 Field Ques1onnaire H1 X H2 X H3 H4 X X X X X X X X chai:: 17 Computer human adapted interac1on research group Preliminary trial Users play the role of a hypothe1cal user at four points in 1me: – first use, seWng several goals; – aper 1 week, to review progress and revise goals as needed; – aper 4 weeks, at the default goal deadline, to review and revise goals; and – aper 1 year (similar to above but for the long term). chai:: Computer human adapted interac1on research group Wellbeing goals •  Steps goal –  Recommended: Walk 10,000 steps/day •  Moderate ac1vity goal –  Recommended: be ac1ve at least 30 minutes per day, in bouts of at least 10 minutes 1 •  Avoid long periods of inac1vity2 –  Recommended: no more than 60 inac1ve minutes in a block 1. W. Haskell, I. Lee, R. Pate, K. Powell, S. Blair, B. Franklin, C. Macera, G. Heath, P. Thompson, and A. Bauman. Physical ac1vity and public health: updated recommenda1on for adults from the American College of Sports Medicine and the American Heart Associa1on. Medicine and science in sports and exercise, 39(8):1423-­‐-­‐1434, 2007. 2. D. Dunstan, B. Kingwell, R. Larsen, G. Healy, E. Cerin, M. Hamilton, J. Shaw, D. Bertovic, P. Zimmet, J. Salmon, et al. Breaking up prolonged siWng reduces postprandial glucose and insulin responses. Diabetes care, 35(5):976-­‐-­‐983, 2012. chai:: 19 Computer human adapted interac1on research group Field trial •  Start of the Field trial •  Week 4 review •  Week 8 Field Ques1onnaire chai:: 20 Computer human adapted interac1on research group Results chai:: Computer human adapted interac1on research group Par1cipants Total 16 Par-cipants Gender Female (5), Male (11) Age 18-­‐30 (5), 31-­‐45(10), >45(1) Educa1on Undergraduate(7), Graduate(9) Technical skill Competent (4), Expert(12) chai:: 22 2
Computer human adapted interac1on research group 2
Key findings – in-­‐lab think aloud •  All par1cipants (N = 16) completed all goal seWng tasks successfully on first aUempt •  Indicated that: –  “Help pop-­‐ups” are useful –  4 wanted to be able to set their own goals –  8 did not value intrinsic factors (commitment, self efficacy….) on first use. chai:: 23 Computer human adapted interac1on research group Changes made to targets chai:: Computer human adapted interac1on research group Field trial results Goals Week 1 Week 4 Step Default: 10,000 steps 3 reduced the target from default 3 increased the target, 2 reduced it Moderate ac1vity Default: 150 minutes per week 2 increased the target, 1 reduced it Avoid inac1vity Default: take breaks every 25 minutes 8 weakened the target with 2 increased it to 60 minutes and 4 set it to 30 minutes 10 weakened it, 2 set it harder target by reducing the period from 60 to 30 minutes. chai:: 25 Computer human adapted interac1on research group Extrinsic elements •  Default dura1on lep at 4 weeks •  2 opted out of receiving email no1fica1on •  5 changed the 1ming for the no1fica1ons chai:: 26 Computer human adapted interac1on research group Intrinsic elements •  Strong posi1ve correla1on between importance and commitment •  Posi1ve correla1on between self efficacy and commitment for Step Goal •  Nega1ve correla1on between difficulty and self efficacy chai:: 27 Computer human adapted interac1on research group Results from Field Ques1onnaire Hypotheses H1 H3 H4 Ques-ons Able to set SMART Goals Easy to set Goals Think more about personal goals Mean 4.22 4.22 3.92 5 point Likert scale: 1 – Strongly disagree, 2 – Disagree, 3-­‐ Neutral, 4 – Agree, 5 – Strongly agree chai:: 28 Computer human adapted interac1on research group Results from Field Ques-onnaire Goal interface survey
Displays helped understand long term trends and
progress
Displays helped understand daily/weekly
progress
Interface helped think more about goals
Interface enabled to set SMART goals
Interface was easy to set goals
3.50 3.60 3.70 3.80 3.90 4.00 4.10 4.20 4.30
Rating average
chai:: Computer human adapted interac1on research group Limita1ons •  User studies : •  Just three goals in health and wellbeing •  Highly educated and technically competent cohort •  Goal representa1on •  Demonstrated only for these 3 health goals chai:: 30 Computer human adapted interac1on research group Summary •  Goals are considered core to user modelling •  Yet, there was no previous theore1cally grounded generic representa1on for modelling user’s goals •  We designed: •  The generic representa1on for long term goals •  Iden1fying addi1onal domain specific aspects •  User interface needed •  Evaluated interface usability and use •  In-­‐lab Think Aloud (16 par1cipants) •  In-­‐the-­‐wild field study (14 par1cipants) chai:: 31 Computer human adapted interac1on research group Ques1ons? Acknowledgement: this work was par1ally funded by CSIRO and the Australian Research Council chai:: Computer human adapted interac1on research group